Consolidating data warehouses
This would require a lot of planning and architecture as typically; the banks are a conglomerate of many entities operating entirely independently at times and often crossing the geographical boundaries.There are thousands of repositories where the data needs to be acquired and standardized in a format that it could be leveraged to obtain meaningful insights.The data warehouse is essential to business intelligence today, allowing organizations to leverage superior analytics to improve customer service, optimize operations and gain competitive advantage.But traditional ETL processes and data loading can be complex, costly and time-consuming.There are now dedicated departments in the companies that deal with data engineering and data science, as a matter of fact, enterprises even have Chief Data Officer and senior executives that deal with business intelligence and data science.Regardless, many companies still struggle with harnessing the power of data value chain due to the bottlenecks introduced by using legacy tools or manual scripts.
Satellite contains temporal and descriptive elements and Links hold the relationships between a hub and a satellite entity.Many organizations have operating units or subsidiaries across various countries or region and extracting the data in a secured fashion from multiple regions or hybrid architectures like on-premises and Cloud can be very cumbersome.Diyotta is the only multiplatform data integration solution which manages data movement in batch and real-time from various source systems, data transformations across various processing engines as well as data loading into multiple end-points with a single, unified software.Based on the normalization concepts, this architecture was introduced by Bill Inmon in late 70s.In a 3NF data warehouse model, various entities are normalized to remove redundancies and then joined together if the data is required across those entities.
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historically however, that is just one form of a data warehouse.